Artificial Intelligence Course in Coimbatore

Introduction to Artificial Intelligence & Machine Learning

AI vs ML vs Deep Learning vs Data Science

Applications of AI & ML  

Introduction to Python

Data Types, Variables, Operators

Control Structures (if, loops)

Functions & Modules

Object-Oriented Programming in Python

Working with Files

Exception Handling

NumPy – Numerical operations

Pandas – Data manipulation

Matplotlib & Seaborn – Data visualization

Scikit-learn – ML library

Jupyter Notebook & Google Colab

Linear Algebra basics 

Probability & Distributions

 Descriptive Statistics 

 Inferential Statistics 

 Calculus for ML

Data Collection & Cleaning

Handling missing values & outliers

Encoding categorical data

Feature scaling (Standardization, Normalization)

Feature selection techniques

Dimensionality reduction (PCA, LDA, t-SNE)

Linear Regression & Multiple Regression

Logistic Regression

Decision Trees & Random Forests

Support Vector Machines (SVM)

K-Nearest Neighbors (KNN)

Naive Bayes Classifier

Model Evaluation: Confusion Matrix, Precision, Recall, F1-Score, ROC-AUC

Clustering Techniques

• K-Means
• Hierarchical Clustering
• DBSCAN

Association Rule Learning (Apriori, Eclat)

Anomaly Detection

Dimensionality Reduction

Introduction to Neural Networks

Perceptron & Multi-Layer Perceptron (MLP)

Activation Functions

Backpropagation & Gradient Descent

Deep Learning with TensorFlow & Keras

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs, LSTM, GRU)

Auto encoders

Transfer Learning

Text Preprocessing (Tokenization, Stopwords, Lemmatization)

Bag of Words, TF-IDF,

Word Embeddings (Word2Vec, GloVe)

Sentiment Analysis

Named Entity Recognition (NER)

Chatbots & Transformer Models (BERT, GPT)

Introduction to RL

Markov Decision Processes (MDP)

Q-Learning

Deep Q-Networks (DQN)

Applications of RL (Games, Robotics, Recommendations)

Explainable AI (XAI)

Generative Models (GANs, VAEs)

Recommendation Systems

AI in Computer Vision (Image Classification, Object Detection)

AI in Speech Recognition

Saving & Loading Models (Pickle, Joblib)

 Model Deployment using Flask / FastAPI

 Deployment on Streamlit / Gradio

 Basics of MLOps (CI/CD, Monitoring)

 Cloud AI services (AWS, GCP, Azure)